Enhanced Clustering Algorithms For Gray-Scale Image Segmentation

Siddiqui, Fasahat Ullah (2012) Enhanced Clustering Algorithms For Gray-Scale Image Segmentation. Masters thesis, Universiti Sains Malaysia.

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Abstract

The clustering algorithms are widely used as an unsupervised method for image segmentation in medical diagnosis, satellite imaging and biometric systems. The algorithms are chosen since they are easy to be implemented, required low computational time and less sensitive to noise and artifacts. However, in some cases the conventional clustering algorithms introduce over-segmentation problems and unable to preserve the region of interest (i.e. objects).

Item Type:	Thesis (Masters)
Subjects:	T Technology > TK Electrical Engineering. Electronics. Nuclear Engineering > TK1-9971 Electrical engineering. Electronics. Nuclear engineering
Divisions:	Kampus Kejuruteraan (Engineering Campus) > Pusat Pengajian Kejuruteraaan Elektrik & Elektronik (School of Electrical & Electronic Engineering) > Thesis
Depositing User:	ASM Ab Shukor Mustapa
Date Deposited:	07 Sep 2018 07:39
Last Modified:	12 Apr 2019 05:26
URI:	http://eprints.usm.my/id/eprint/41804

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